System and method for obtaining video for use with photo-based estimation

ABSTRACT

A server comprises a communications module, a processor coupled to the communications module, and a memory coupled to the processor. The memory stores processor-executable instructions which, when executed by the processor, configure the processor to receive, via the communications module and from a remote computing device, video data of a vehicle in an original state, store, in the memory, at least some of the video data of the vehicle and associate the stored video data with an account, receive, via the communications module and from the remote computing device, an indication of a claim, the indication associated with an account identifier, retrieve, using the account identifier and from the memory, the video data of the vehicle in the original state from the memory, and send, via the communications module and to the remote computing device, instructions for obtaining video data of the vehicle based on the video data of the vehicle in the original state.

TECHNICAL FIELD

The present application relates to automated processing of claims and,more particularly, to systems and methods for use with photo-based claimprocessing.

BACKGROUND

When a party wishes to make an insurance claim, that party may contactan insurer by telephone and the insurer may assign a claims adjuster tothe claim. The claims adjuster evaluates the claim. In order to evaluatethe claim, the claims adjuster may inspect property, such as a vehicle,that is associated with the claim. The claim adjustment process may takea considerable amount of time and effort.

Computers have sometimes been used to improve the claims process. Forexample, some insurers may provide a web interface that allows forsubmission of an online claim form. Typically, online claim submissionsare routed to a claims adjuster. This claim adjustment process may alsobe time consuming and result in a large delay prior to processing of aclaim.

Photo-based estimation has been used to improve the claims process.Photo-based estimation involves a customer uploading an image which canbe used for damage estimation. Photo-based estimation may lead tofraudulent claims being submitted as images are easy to fake ormanipulate. For example, a user may upload an image of a vehicle thatwas retrieved over the internet, rather than an image captured using theuser's camera. As another example, an image editing tool may be used tomanipulate an image.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are described in detail below, with reference to thefollowing drawings:

FIG. 1 is a schematic operation diagram illustrating an operatingenvironment of an example embodiment;

FIG. 2 is a simplified schematic diagram showing components of acomputing device;

FIG. 3 is high-level schematic diagram of an example computing device;

FIG. 4 shows a simplified organization of software components stored ina memory of the example computing device of FIG. 3;

FIG. 5 is a flowchart showing operations performed by a server inrouting a claim;

FIG. 6 is an example screen of a graphical user interface;

FIG. 7 is an example screen of a graphical user interface;

FIG. 8 is a flowchart showing operations performed by a server forperforming photo-based estimation;

FIG. 9 is an example screen of a graphical user interface;

FIGS. 10A to 10D are example screens of graphical user interfaces;

FIGS. 11A and 11B are example screens of graphical user interfaces;

FIG. 12 is an example screen of a graphical user interface;

FIG. 13 is a flowchart showing operations performed by a server foronboarding a vehicle;

FIG. 14 is an example screen of a graphical user interface;

FIG. 15 is a flowchart showing operations performed by a server fordetermining an original state of a vehicle;

FIG. 16 is an example screen of a graphical user interface; and

FIG. 17 is a flowchart showing operations performed by a server forinstructing a user to obtain video data.

Like reference numerals are used in the drawings to denote like elementsand features.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

According to an aspect, there is provided a server. The server comprisesa communications module and a data store storing profiles for parties.The server comprises a processor coupled to the communications moduleand the data store and a memory coupled to the processor. The memorystores processor-executable instructions which, when executed by theprocessor, configure the processor to receive, via the communicationsmodule and from a remote computing device, a signal representing anindication of a damage location of a vehicle; send, via thecommunications module and to the remote computing device, instructionsfor obtaining video data of the vehicle based on the damage location;receive, via the communications module and from the remote computingdevice, video data of the vehicle; and process the video data to confirman identity of the vehicle and to numerically quantify an amount ofdamage to the vehicle.

In one or more aspects, the instructions for obtaining video data of thevehicle include an indication of a starting point and an ending pointfor video capture.

In one or more aspects, the instructions for obtaining video data of thevehicle include instructions for capturing an identifier of the vehicle.

In one or more aspects, the identifier includes one of a vehicleidentification number (VIN) and a license plate number.

In one or more aspects, processing the video data to confirm an identityof the vehicle comprises comparing the identifier of the vehicle to adatabase record.

In one or more aspects, the instructions for obtaining video data of thevehicle include at least one of text instructions, photo instructionsand video instructions.

In one or more aspects, the video data of the vehicle is received as astream and the processor-executable instructions, when executed by theprocessor, further configure the processor to evaluate progress of videodata capture by the remote computing device; and send, via thecommunications module and to the remote computing device, an indicationof the progress.

In one or more aspects, the processor-executable instructions, whenexecuted by the processor, further configure the processor to send, viathe communications module and to the remote computing device, a requestto segment the video data into at least an identity portion and a damageportion.

In one or more aspects, processing the video data to confirm an identityof the vehicle comprises processing the identity portion and whereinprocessing the video data to numerically quantify the amount of damageto the vehicle comprises processing the damage portion.

In one or more aspects, the identity portion is an image obtained fromthe video data.

According to a further aspect, there is provided a method. The methodcomprises receiving, via a communications module and from a remotecomputing device, a signal representing an indication of a damagelocation of a vehicle; sending, via the communications module and to theremote computing device, instructions for obtaining video data of thevehicle based on the damage location; receiving, via the communicationsmodule and from the remote computing device, video data of the vehicle;and processing the video data to confirm an identity of the vehicle andto numerically quantify an amount of damage to the vehicle.

In one or more aspects, the instructions for obtaining video data of thevehicle include an indication of a starting point and an ending pointfor video capture.

In one or more aspects, the instructions for obtaining video data of thevehicle include instructions for capturing an identifier of the vehicle.

In one or more aspects, the identifier includes one of a vehicleidentification number (VIN) and a license plate number.

In one or more aspects, processing the video data to confirm an identityof the vehicle comprises comparing the identifier of the vehicle to adatabase record.

In one or more aspects, the instructions for obtaining video data of thevehicle include at least one of text instructions, photo instructionsand video instructions.

In one or more aspects, the video data of the vehicle is received as astream and the method further comprises evaluating progress of videodata capture by the remote computing device; and sending, via thecommunications module and to the remote computing device, an indicationof the progress.

In one or more aspects, the method further comprises sending, via thecommunications module and to the remote computing device, a request tosegment the video data into at least an identity portion and a damageportion.

In one or more aspects, processing the video data to confirm an identityof the vehicle comprises processing the identity portion and whereinprocessing the video data to numerically quantify the amount of damageto the vehicle comprises processing the damage portion.

In a further aspect, there is provided a non-transitory computerreadable storage medium comprising computer-executable instructionswhich, when executed, configure a computing device to receive, via acommunications module and from a remote computing device, a signalrepresenting an indication of a damage location of a vehicle; send, viathe communications module and to the remote computing device,instructions for obtaining video data of the vehicle based on the damagelocation; receive, via the communications module and from the remotecomputing device, video data of the vehicle; and process the video datato confirm an identity of the vehicle and to numerically quantify anamount of damage to the vehicle.

In a further aspect, there is provided a server. The server comprises acommunications module; a processor coupled to the communications module;and a memory coupled to the processor, the memory storingprocessor-executable instructions which, when executed by the processor,configure the processor to receive, via the communications module andfrom a remote computing device, video data of a vehicle in an originalstate; store, in the memory, at least some of the video data of thevehicle and associate the stored video data with an account; receive,via the communications module and from the remote computing device, anindication of a claim, the indication associated with an accountidentifier; retrieve, using the account identifier and from the memory,the video data of the vehicle in the original state from the memory; andsend, via the communications module and to the remote computing device,instructions for obtaining video data of the vehicle based on the videodata of the vehicle in the original state.

In one or more aspects, the indication of the claim includes anindication of a damage location of the vehicle.

In one or more aspects, the instructions for obtaining video data of thevehicle include instructions for obtaining video data of the vehicle atthe damage location.

In one or more aspects, the instructions for obtaining video data of thevehicle include an indication of a starting point and an ending pointfor video capture.

In one or more aspects, the instructions for obtaining video data of thevehicle include instructions for capturing an identifier of the vehicle.

In one or more aspects, the processor-executable instructions, whenexecuted by the processor, further configure the processor to receive,via the communications module and from the remote computing device,video data of the vehicle captured in response to the instructions; andprocess the video data to numerically quantify an amount of damage tothe vehicle.

In one or more aspects, the processor-executable instructions, whenexecuted by the processor, further configure the processor to receive,via the communications module and from the remote computing device,video data of the vehicle captured in response to the instructions; andprocess the video data to confirm an identity of the vehicle.

In one or more aspects, the processor-executable instructions, whenexecuted by the processor, further configure the processor to processthe video data of the vehicle in the original state to identify at leastone of pre-existing damage to the vehicle and aftermarket modificationsmade to the vehicle.

In one or more aspects, the processor-executable instructions, whenexecuted by the processor, further configure the processor to generate athree-dimensional model of the vehicle based at least on the video dataof the vehicle in the original state.

In one or more aspects, the instructions for obtaining video data of thevehicle are further based on the three-dimensional model of the vehicle.

In a further aspect, there is provided a method. The method comprisesreceiving, via a communications module and from a remote computingdevice, video data of a vehicle in an original state; storing at leastsome of the video data of the vehicle in memory and associating thestored video data with an account; receiving, via the communicationsmodule and from the remote computing device, an indication of a claim,the indication associated with an account identifier; retrieving, usingthe account identifier and from the memory, the video data of thevehicle in the original state from the memory; and sending, via thecommunications module and to the remote computing device, instructionsfor obtaining video data of the vehicle based on the video data of thevehicle in the original state.

In one or more aspects, the instructions for obtaining video data of thevehicle include instructions for obtaining video data of the vehicle atthe damage location.

In one or more aspects, the instructions for obtaining video data of thevehicle include an indication of a starting point and an ending pointfor video capture.

In one or more aspects, the instructions for obtaining video data of thevehicle include instructions for capturing an identifier of the vehicle.

In one or more aspects, the method further comprises receiving, via thecommunications module and from the remote computing device, video dataof the vehicle captured in response to the instructions; and processingthe video data to numerically quantify an amount of damage to thevehicle.

In one or more aspects, the method further comprises receiving, via thecommunications module and from the remote computing device, video dataof the vehicle captured in response to the instructions; and processingthe video data to confirm an identity of the vehicle.

In one or more aspects, the method further comprises processing thevideo data of the vehicle in the original state to identify at least oneof pre-existing damage to the vehicle and aftermarket modifications madeto the vehicle.

In one or more aspects, the method further comprises generating athree-dimensional model of the vehicle based at least on the video dataof the vehicle in the original state.

In one or more aspects, the instructions for obtaining video data of thevehicle are further based on the three-dimensional model of the vehicle.

In a further aspect, there is provided a non-transitory computerreadable storage medium comprising computer-executable instructionswhich, when executed, configure a computing device to receive, via acommunications module and from a remote computing device, video data ofa vehicle in an original state; store, in memory, at least some of thevideo data of the vehicle and associate the stored video data with anaccount; receive, via the communications module and from the remotecomputing device, an indication of a claim, the indication associatedwith an account identifier; retrieve, using the account identifier andfrom the memory, the video data of the vehicle in the original statefrom the memory; and send, via the communications module and to theremote computing device, instructions for obtaining video data of thevehicle based on the video data of the vehicle in the original state.

Photo-based claims estimation techniques are described herein. Forexample, a remote computing device, such as a smartphone, may be used tosubmit a claim to a remote server. During the claim submission,photo-based estimation may be employed to automatically evaluate andprocess at least some claims. Photo-based estimation allows forautomated adjudication of a claim based on video or image data obtainedusing the remote computing device. More specifically, video or imagedata may be algorithmically analyzed to quantify an amount of damage toinsured property, such as an insured vehicle, and to automaticallydetermine a repair or replacement cost for the insured property.Further, video or image data may be analyzed to confirm an identity ofthe insured property.

Conveniently, where photo-based estimation is employed, claim adjustmentmay be provided automatically and in real time. For example, aprocessing server may automatically send instructions for obtainingvideo or image data of an insured vehicle and, upon receiving the videoor image data, the processing server may evaluate the video or imagedata in order to confirm an identity of an insured vehicle, quantify anamount of damage to the insured vehicle and may then automaticallypropose a settlement amount based on the amount of damage.

As another example, a processing server may automatically sendinstructions for obtaining video data of damage made to an insuredvehicle. The processing server may analyze the video data in order toconfirm an identity of an insured vehicle, quantify an amount of damageto the insured vehicle and may automatically propose a settlement amountbased on the amount of damage. By requiring the user to obtain videodata, risk of fraud is reduced as video data is more difficult to edit,fake, or manipulate compared to image data.

Other aspects and features of the present application will be understoodby those of ordinary skill in the art from a review of the followingdescription of examples in conjunction with the accompanying figures.

In the present application, the term “and/or” is intended to cover allpossible combinations and sub-combinations of the listed elements,including any one of the listed elements alone, any sub-combination, orall of the elements, and without necessarily excluding additionalelements.

In the present application, the phrase “at least one of . . . and . . .” is intended to cover any one or more of the listed elements, includingany one of the listed elements alone, any sub-combination, or all of theelements, without necessarily excluding any additional elements, andwithout necessarily requiring all of the elements.

FIG. 1 is a schematic operation diagram illustrating an operatingenvironment of an example embodiment.

As illustrated, a server 160 and a remote computing device 100, such asa smartphone, communicate via a network 120.

The remote computing device 100 and the server 160 may be ingeographically disparate locations. Put differently, the remotecomputing device 100 may be remote from the server 160.

The remote computing device 100 and the server 160 are computer systems.The remote computing device 100 may take a variety of forms including,for example, a mobile communication device such as a smartphone, atablet computer, a wearable computer such as a head-mounted display orsmartwatch, a laptop or desktop computer, or a computing device ofanother type.

The remote computing device 100 is adapted to present a graphical userinterface that allows for remote submission of a claim to the server160. For example, the remote computing device 100 may be adapted tosubmit claim information through a chat interface and/or mobileapplication that may be provided on the remote computing device 100. Byway of example, the claim information may include video or image dataassociated with the claim. The video or image data may represent aportion of an insured vehicle, for example.

As further described below, the server 160 is adapted to performautomated claim processing of at least some claims. For example, theserver 160 may be a claims processing server, which may also be referredto as a processing server, which is configured to selectively performphoto-based estimation. In doing so, the server 160 may receive video orimage data of at least a portion of a vehicle and may analyze the videoor image data to confirm an identity of the vehicle and to automaticallydetermine a value associated with a claim. For example, the server 160may automatically determine an estimate of a repair or replacement costassociated with the claim based on the video or image data and mayprovide the estimate to the remote computing device 100 for display.Operations associated with the server 160 will be described in greaterdetail below.

The network 120 is a computer network. In some embodiments, the network120 may be an internetwork such as may be formed of one or moreinterconnected computer networks. For example, the network 120 may be ormay include an Ethernet network, an asynchronous transfer mode (ATM)network, a wireless network, a telecommunications network or the like.

As further explained below, the remote computing device 100 communicateswith the server 160 via the network 120 in order to allow for a claimsubmitted by the remote computing device 100 to be automaticallyprocessed by the server 160. That is, in at least some embodiments, theserver 160 may process the claim without any human intervention.

As illustrated in FIG. 1, the server 160 and/or the remote computingdevice 100 may also communicate with an operator device 150. Theoperator device 150 is or includes a computing device.

The operator device 150 is adapted to be operated by an operator, whomay be a claims processor. In at least some embodiments, the operatordevice 150 may only be engaged when the server 160 determines thatautomated claims processing, such as photo-based estimation, is notavailable. For example, when the server 160 determines that automatedclaims processing is not available (e.g., if the risk of usingphoto-based estimation is too high, if images appear to have beentampered with, etc.), it may hand off a chat session between a chat-boton the server 160 and a user on the remote computing device 100 to theoperator device 150 so that an operator may engage in a remote chat withthe user via the network 120. When the server 160 hands off the chatsession, it may do so unbeknownst to the user. That is, the chat-bot maysimply cease operating and the operator may take over seamlessly. Tofacilitate such handoff, the server 160 may provide the operator device150 with a chat history when the chat session is handed over to theoperator device 150.

Accordingly, the operator device 150 may communicate with one or both ofthe server 160 and the remote computing device 100 via the network 120.

FIG. 2 is a simplified schematic diagram showing components of theremote computing device 100.

The remote computing device 100 may include modules including, asillustrated, for example, one or more displays 210, a video capturemodule 230, a sensor module 240, and a computing device 250.

The one or more displays 210 are a display module. The one or moredisplays 210 are used to display user interface screens that may beused, for example, to submit a claim to the server 160 (FIG. 1). The oneor more displays 210 may be internal displays of the remote computingdevice 100 (e.g., disposed within a body of the remote computingdevice).

The video capture module 230 may be or may include a camera. The videocapture module may be used to obtain video data, such as videos, andimage data, such as images. As will be described in greater detailherein, video or image data obtained by the video capture module 230 maybe used for photo-based estimation during processing of a claim. Thevideo capture module 230 may be or may include a digital image sensorsystem as, for example, a charge coupled device (CCD) or a complementarymetal-oxide-semiconductor (CMOS) image sensor.

The video capture module 230 and the display 210 may cooperate in atleast one operating mode of the remote computing device 100 to provide aviewfinder. The viewfinder may display camera data obtained via thevideo capture module 230 in real time or near real time on the display210.

The sensor module 240 may be a sensor that generates sensor data basedon a sensed condition. By way of example, the sensor module 240 may beor include a location subsystem which generates sensor data that is alocation. The location may be the current geographic location of theremote computing device 100. The location subsystem may be or includeany one or more of a global positioning system (GPS), an inertialnavigation system (INS), a wireless (e.g., cellular) triangulationsystem, a beacon-based location system (such as a Bluetooth low energybeacon system), or a location subsystem of another type.

The computing device 250 is in communication with the one or moredisplays 210, the video capture module 230, and the sensor module 240.The computing device 250 may be or may include a processor which iscoupled to the one or more displays 210, the video capture module 230,and/or the sensor module 240.

FIG. 3 is a high-level operation diagram of an example computing device300. In some embodiments, the example computing device 300 may beexemplary of the computing device 250 (FIG. 2) and/or the server 160(FIG. 1) and/or the operator device 150 (FIG. 1).

The example computing device 300 includes a variety of modules. Forexample, as illustrated, the example computing device 300 may include aprocessor 310, a memory 320, a communications module 330, and/or astorage module 340. As illustrated, the foregoing example modules of theexample computing device 300 are in communication over a bus 350.

The processor 310 is a hardware processor. The processor 310 may, forexample, be one or more ARM, Intel x86, PowerPC processors or the like.

The memory 320 allows data to be stored and retrieved. The memory 320may include, for example, random access memory, read-only memory, andpersistent storage. Persistent storage may be, for example, flashmemory, a solid-state drive or the like. Read-only memory and persistentstorage are a non-transitory computer-readable storage medium. Acomputer-readable medium may be organized using a file system such asmay be administered by an operating system governing overall operationof the example computing device 300.

The communications module 330 allows the example computing device 300 tocommunicate with other computing devices and/or various communicationsnetworks. For example, the communications module 330 may allow theexample computing device 300 to send or receive communications signals.Communications signals may be sent or received according to one or moreprotocols or according to one or more standards. For example, thecommunications module 330 may allow the example computing device 300 tocommunicate via a cellular data network, such as for example, accordingto one or more standards such as, for example, Global System for MobileCommunications (GSM), Code Division Multiple Access (CDMA), EvolutionData Optimized (EVDO), Long-term Evolution (LTE) or the like.Additionally or alternatively, the communications module 330 may allowthe example computing device 300 to communicate using near-fieldcommunication (NFC), via Wi-Fi™, using Bluetooth™ or via somecombination of one or more networks or protocols. In some embodiments,all or a portion of the communications module 330 may be integrated intoa component of the example computing device 300. For example, thecommunications module may be integrated into a communications chipset.In some embodiments, the communications module 330 may be omitted suchas, for example, if sending and receiving communications is not requiredin a particular application.

The storage module 340 allows the example computing device 300 to storeand retrieve data. In some embodiments, the storage module 340 may beformed as a part of the memory 320 and/or may be used to access all or aportion of the memory 320. Additionally or alternatively, the storagemodule 340 may be used to store and retrieve data from persisted storageother than the persisted storage (if any) accessible via the memory 320.In some embodiments, the storage module 340 may be used to store andretrieve data in a database. A database may be stored in persistedstorage. Additionally or alternatively, the storage module 340 mayaccess data stored remotely such as, for example, as may be accessedusing a local area network (LAN), wide area network (WAN), personal areanetwork (PAN), and/or a storage area network (SAN). In some embodiments,the storage module 340 may access data stored remotely using thecommunications module 330. In some embodiments, the storage module 340may be omitted and its function may be performed by the memory 320and/or by the processor 310 in concert with the communications module330 such as, for example, if data is stored remotely. The storage modulemay also be referred to as a data store.

Software comprising instructions is executed by the processor 310 from acomputer-readable medium. For example, software may be loaded intorandom-access memory from persistent storage of the memory 320.Additionally or alternatively, instructions may be executed by theprocessor 310 directly from read-only memory of the memory 320.

FIG. 4 depicts a simplified organization of software components storedin the memory 320 of the example computing device 300 (FIG. 3). Asillustrated, these software components include an operating system 400and an application 410.

The operating system 400 is software. The operating system 400 allowsthe application 410 to access the processor 310 (FIG. 3), the memory320, and the communications module 330 of the example computing device300 (FIG. 3). The operating system 400 may be, for example, Google™Android™, Apple™ iOS™, UNIX™, Linux™, Microsoft™ Windows™, Apple OSX™ orthe like.

The application 410 adapts the example computing device 300, incombination with the operating system 400, to operate as a deviceperforming a particular function. For example, the application 410 maycooperate with the operating system 400 to adapt a suitable embodimentof the example computing device 300 to operate as the computing device250 (FIG. 2) of the remote computing device 100 (FIG. 1) or as theserver 160 (FIG. 1) or as the operator device 150 (FIG. 1).

Where the application 410 is provided on the remote computing device100, the application may be a submission application, which may also bereferred to as a claim submission application. The application 410 maybe a web-based or standalone application. The application 410 may beconfigured to engage in an authenticated session with the server 160.The authenticated session may occur, for example, after the remotecomputing device 100 has validly authenticated itself to the server 160using, for example, one or more credentials. During the authenticatedsession, the remote computing device 100 may engage in encryptedcommunications with the server 160. For example, as will be describedbelow, the remote computing device 100 may send, via the communicationsmodule, video or image data to the server 160 and the server may analyzethe video or image data to automatically process a claim (i.e., usingphoto-based estimation). The video or image data may be sent in anencrypted format. Conveniently, the encrypting of the video or imagedata may ensure that the server 160 only receives and processes videosfrom authentic submission applications. Non-authentic submissionapplications cannot submit such video or image data since they are notable to encrypt the video or image data in a format that would berecognized or accepted by the server 160.

Where the application 410 is provided on the server 160, the application410 may include a plurality of software modules associated with claimprocessing. For example, a fraud detection module may includecomputer-executable instructions for identifying possible fraudulentclaims based on the video or image data, a vehicle detection module mayinclude computer-readable instructions for identifying a vehicle usingvideo or image data, an instruction module may includecomputer-executable instructions for generating or retrievinginstructions on how to obtain video or image data of a vehicle, a claimrouting module may include computer-executable instructions fordetermining whether photo-based estimation is to be used or whethermanual estimation is to be used, a photo-based estimation module may beused for processing a claim using photo-based estimation techniques,and/or a manual estimation module may be used for engaging an operatordevice 150 (FIG. 1) to process a claim manually. Other modules apartfrom those listed above may be included instead of or in addition to themodules identified and the functions described as being attributed to aspecific module may instead be provided by another module. Further, oneor more of the modules may not be included in the application 410 and/ormay not be provided by the server 160 itself. For example, the server160 may cooperate with other servers or computer systems which mayprovide some such functions.

At least some components illustrated in FIG. 3 or FIG. 4 may takedifferent forms depending on which of the computing devices they areprovided on. For example, a server 160 may include or have access to astorage module 340 (which may also be referred to as a data store) whichhas stored thereon profiles for a plurality of parties, who may also bereferred to as users or customers. The users may be insured persons, forexample. The profiles may be or include policy data such as insurancepolicy data. The insurance policy data may be stored as a databaserecord. The insurance policy data may specify information associatedwith an insurance policy which may, for example, be a vehicle insurancepolicy for an insured vehicle. The insurance policy data may, forexample, include identification information or data for an insuredperson or an insured vehicle. By way of example, the insurance policydata for a given one of the profiles may specify vehicle identifyingdata for an insured vehicle. By way of example, the insurance policydata may specify a vehicle type of an insured vehicle. The vehicle typemay be or include one or more of an indication of whether the vehicle isa car, an indication of whether the vehicle is a truck, an indication ofwhether the vehicle is a sports utility vehicle, an indication ofwhether the vehicle is a motorcycle, a make of the vehicle (e.g., amanufacturer name), a model of the vehicle (e.g., a model name), a yearof the vehicle (e.g., a year or production or “model year” of thevehicle), a trim line indication for the vehicle (which may also bereferred to as a grade of the vehicle or trim level), an indication of apaint colour, and/or an indication of an aftermarket modification (whichmay indicate whether any aftermarket modifications have been performedon the vehicle (e.g., lowering the car, adding a spoiler, etc.).

Alternatively or additionally, the insurance policy data may specify anyone or more of: a vehicle identification number (VIN) for an insuredvehicle, a policy identifier associated with a profile (e.g., aninsurance policy number), one or more user identifiers (e.g., a name,address and/or contact information) and/or a location.

The profiles may also include other information or data about an insuredvehicle. For example, a logo (such as a manufacturer logo), a vehiclebody template, and/or a three-dimensional vehicle model may be includedin one or more of the profiles. Some such data may be used, for example,to evaluate a claim. For example, a logo displayed in an image submittedto the server 160 by the remote computing device 100 may be used todetermine whether the image is of an insured vehicle. For example, thelogo may be compared with the logo in the profile.

It will be appreciated that at least some of the information describedabove as being provided in the profile may, instead, be stored elsewhereand may be retrieved based on data in an active profile. For example,the server 160 may determine that a user is associated with a particularone of the profiles and may retrieve one or more of a VIN, a year, amake and a model of an insured vehicle from that profile. The server 160may then use the VIN, year, make and/or model to determine furtherinformation about the vehicle, such as the logo, vehicle body templateand/or three-dimensional vehicle model.

In some embodiments, the profiles may store an indication of whether acustomer is eligible for photo-based estimation. The indication may, forexample, be a flag. The flag may be considered by the server 160 whenthe server 160 determines whether a claim should be routed tophoto-based estimation or whether the claim should be routed to manualestimation.

The storage module 340 may, in some embodiments, store a set of makesand models that are or are not eligible for photo-based estimation. Forexample, a whitelist and/or blacklist of vehicle types may be stored.The whitelist may indicate vehicle types that are eligible forphoto-based estimation and the blacklist may indicate vehicle types thatare not eligible for photo-based estimation. The server 160 may use thewhitelist or blacklist in determining whether photo-based estimationshould be used to automatically process a claim.

Each profile may be associated with one or more credential that may bestored therewith. The credential may be or include any one or more of: atoken, a policy identifier, a user name, a personal identificationnumber (PIN), biometric data, and/or a password. The credential may beused by the server 160 to authenticate the remote computing device 100.More specifically, the credential may be used to determine that theremote computing device 100 is being operated by an authorized user andto identify a profile that is to be used while interacting with thatuser via the remote computing device 100 (i.e., to identify an “active”profile).

The storage module 340 may store data representing preferred scenes forvehicles for a plurality of vehicle types. The preferred scenes may eachbe associated with a vehicle type and a damage location. For example, agiven one of the preferred scenes may be associated with damage near afront left wheel for a particular make of vehicle. The data regardingthe preferred scenes may, for example, reflect a base vehicle and thedata regarding the preferred scenes may be used to aid a user incapturing video or image data of a vehicle that will be suitable forphoto-based estimation. For example, instructions may be sent to theuser to aid the user in capturing video data of the vehicle. As will bedescribed in more detail below, the instructions may be selected basedon what part of the vehicle is damaged.

Operations performed by the remote computing device 100 and the server160 will now be described.

FIG. 5 is a flowchart showing a method 500 for routing a claim. Theoperations in method 500 are performed by server 160. More specifically,computer-executable instructions stored in memory of the server 160 may,when executed by a processor of the server 160, configure the server 160to perform the method 500 or a portion thereof.

Method 500 begins when a request is received, via the communicationsmodule and from a remote computing device, to initiate a chat session(step 510). In this embodiment, the chat session may be initiated by auser of the remote computing device to start a new claim. The chatsession may be requested through an internet interface, mobileapplication, etc.

In response, the server 160 provides a chat interface to the remotecomputing device 100 (step 520). In this embodiment, the server 160sends, via a communications module and to the remote computing device,data that includes a chat interface.

An example chat interface 600 is shown in FIG. 6. The chat interfaceallows a user of the remote computing device 100 to send instant textmessages to the server 160. The server 160 receives such messages anduses a chat bot to respond to such messages. The chat bot analyzes themessages to extract data from such messages and/or to formulate and senda reply to such messages. The chat bot may, for example, automaticallyengage in a dialogue with the server 160 in an attempt to obtain dataregarding a claim. For example, the chat bot may attempt to obtainanswers to one or more predetermined questions that may be used forclaim routing purposes.

The server 160 may be equipped with a natural language processing enginewhich may be used to interpret messages received from the remotecomputing device 100. In the example shown in FIG. 6, the server 160receives, from the remote computing device 100, a message indicatingthat a user of the remote computing device 100 was in an accident. Inresponse, the server 160 analyzes the message and determines, from themessage, that a user has a claim to submit (e.g. by determining that theuser has been in an accident). The server 160 may then consult apredetermined question list to identify a question to send to the remotecomputing device 100. The identified question, in the example, is “areyou alright”. The server 160 may continue to receive answers toquestions and may send replies, which may be additional questions, tothe remote computing device 100. The server 160 may, therefore, engagein a chat with the remote computing device 100 which may, in someexample embodiments, appear to a user of the remote computing device toinvolve a human operator but which, in fact involves a chat bot. Inother embodiments, the remote computing device 100 may be informed thatit is engaging with a chat bot and may generate an output, such as adisplay, which informs a user of the chat-bot.

The chat-bot may, therefore, be configured to prompt a user of theremote computing device 100 to input one or more data points that may beused to automatically evaluate a claim, as will be described in moredetail below.

Once the chat interface is initiated, the server 160 continues toreceive, via the communications module and from the remote computingdevice 100, data including input received at the remote computing devicethrough the chat interface. The chat interface provides a free-forminput interface which allows for the input of information via text orspeech and the chat bot may perform natural language processing toidentify relevant information.

During the chat session, the server 160 requests and receives anidentifier from the user (step 530). In the example shown in FIG. 6, theserver 160 asks the user to provide a policy number. As will beappreciated, the chat may prompt the user to provide other identifierssuch as a name, address, contact information, etc. Other examples may beone or more of a token, a PIN, a user name, biometric data, and/or apassword.

Those skilled in the art will appreciate that although, in FIG. 6, thecredential is received within the chat interface, the credential may bereceived outside of the chat interface. For example, a submissionapplication on the remote computing device 100 may provide a token tothe server 160 or a password to the server 160. As another example, theuser may open a mobile application on the remote computing device 100which may retrieve a previously stored username and password andautomatically log the user in. Upon login, the chat interface may beprovided.

The server 160 retrieves insurance policy data based on the receivedidentifier (step 540). In this embodiment, the insurance policy dataincludes one or more identifiers of a vehicle associated with theinsurance policy data and one or more identifiers of a user associatedwith the insurance policy data. The identifiers of the vehicle may bethe VIN, the make, the model and/or the year of the insured vehicle. Theidentifier of the user may be the first name, last name, phone numberand/or address. Other examples of insurance policy data that may beretrieved or obtained is described in greater detail above.

In the example shown in FIG. 6, an account has been identified based onthe policy number and insurance policy data is obtained. The server 160automatically retrieves the first name of the user associated with theinsurance policy data and asks the user to confirm their identity.

Once the insurance policy data has been retrieved, the server 160obtains a three-dimensional (3D) vehicle model of the insured vehicle(step 550). The 3D vehicle model may be obtained from a data store thatstores a plurality of 3D vehicle models. Each 3D vehicle model may beassociated with a particular type of vehicle and, in identifying the 3Dvehicle model, the server 160 may first identify a vehicle type from theinsurance policy data. The vehicle type may be one or more of a car, atruck, a sports utility vehicle, a motorcycle, a make of the vehicle, amodel of the vehicle, a year of the vehicle, a trimline of the vehicle,and/or an indication of an aftermarket modification of the vehicle.After identifying the vehicle type of the insured vehicle from theidentified profile, the server 160 may then retrieve thethree-dimensional vehicle model from a vehicle model database based onthe vehicle type.

In some instances, the retrieved 3D vehicle model may represent the samevehicle as the insured vehicle (i.e., the same year, make and model). Inother embodiments, the retrieved 3D vehicle model may be of a similar(but not the same) vehicle to the insured vehicle. For example, thevehicle may be of a common type (e.g., an SUV where the insured vehicleis an SUV). As will be described in more detail, the retrieved 3Dvehicle model may be a 3D vehicle model of the vehicle generated duringonboarding.

In some instances, the server 160 may have access to redesign timelinedata. The redesign timeline data may, for example, indicate years when avehicle underwent a redesign (as opposed to a minor refresh which occursin most model years). That is, the redesign timeline data may definevehicle generations. A vehicle generation is represented by date rangeswhich indicate the times when the vehicle had a generally common design.When a redesign occurs, a new vehicle generation begins.

The redesign timeline data may be used by the server 160 when selectingan appropriate 3D vehicle model. For example, when selecting anappropriate 3D model to use for a given insured vehicle, the server 160may prefer to select a 3D vehicle model that is within a same vehiclegeneration as the insured vehicle. The server 160 may be configured to,for example, select a 3D vehicle model of a vehicle that is of the samevehicle generation as an insured vehicle, even if there is another 3Dvehicle model of a vehicle that has a closer model year but that is of adifferent vehicle generation. For example, if 3D vehicle models areavailable for a particular vehicle in 2012 and 2018 and an insuredvehicle is a 2017 vehicle, and if the redesign timeline data indicatesthat a redesign occurred in 2018, the server 160 may select the 2012version of the 3D vehicle model.

Once the 3D vehicle model is obtained, the server 160 sends, via thecommunications module to the remote computing device, display data thatincludes the 3D vehicle model (step 560). In this embodiment, the 3Dvehicle model may be displayed as a message below a last messagedisplayed in the chat interface. The display data may also include adamage location indicator overlaid on the three-dimensional vehiclemodel. The damage location indicator is selectable by the user of theremote computing device to input an indication of a damage location.

The display data may include a graphical user interface that allows forinteraction with the 3D vehicle model. An example of one such graphicaluser interface is shown in display screen 700 in FIG. 7. As can be seen,display screen 700 includes a graphical user interface 710 that includesa 3D vehicle model 720 and a damage location indicator 730.

The graphical user interface 710 may allow for rotation of the 3Dvehicle model 720. For example, the vehicle may be rotated on thedisplay by selecting an area associated with the vehicle and moving apointing device (such as a finger) in a direction of rotation after suchselection. Touch gestures may, for example, be used to control an angleof rotation associated with the 3D vehicle model. The three-dimensionalmodel may be rendered using OpenGL ES, for example.

The damage location indicator 730 is overlaid on the 3D vehicle model720. The damage location indicator 730 is selectable by a user via aninput interface (such as a touchscreen) associated with the remotecomputing device 100. The damage location indicator may include aplurality of selectable locations. Each selectable location may beassociated with location information defining a location. For example,the plurality of selectable locations may be or include a grid.

In some instances, the display data may include a selectable option totoggle between 2D and 3D viewing. In some embodiments, the display datamay allow a user to indicate a location in 2D by selecting for example,three planes and adjusting accordingly. In such instances, there may bea selectable feature or gesture which allows the user to toggle betweenthe 2D and 3D views. In some instances, the views may be displayed inplanes perpendicular to the plane being set. In some instances, theplane being set may be highlighted on the visual interface in the chatsession for the user to interact with.

The remote computing device 100 receives the display data and displaysthe 3D vehicle model and the damage location indicator overlaid thereon.An input may be received at the remote computing device 100 via theinput interface. The input may be a selection of the damage locationindicator. The selection may be made, for example, using force touch(iOS) or double tap (Android) or using other gestures. After receivingthe input, the remote computing device 100 may send the indication ofthe damage location to the server 160. The server 160 may use theindication of the damage location to facilitate photo-based claimprocessing according to a method 800 shown in FIG. 8. The operations inmethod 800 are performed by server 160. More specifically,computer-executable instructions stored in memory of the server 160 may,when executed by a processor of the server 160, configure the server 160to perform the method 800 or a portion thereof.

Method 800 begins when the server 160 receives, from the remotecomputing device 100, an indication of a damage location of a vehicle(step 810). The indication of the damage location may be based on aselection of one of a plurality of locations specified in the damagelocation indicator. The indication of the damage location may indicate,to the server 160, a location where a vehicle has sustained damage. Inone example, the indication of the damage location may indicate a side(e.g., left, right, front, back) associated with the damage. As will beappreciated, multiple damage locations may also be indicated.

Using the instructions module, the server 160 obtains instructions forobtaining video data of the vehicle based on the damage location andsends the instructions to the remote computing device 100 (step 820). Inthis embodiment, the instructions for obtaining video data may beobtained from a data store that stores a plurality of instruction sets.Each instruction set may be associated with a particular damage locationand/or a particular vehicle type. Each instruction set may include astarting point and an ending point for obtaining video data of thevehicle at the damage location. Each instruction set may be videoinstructions, photo instructions and/or text instructions. In the eventthat multiple damage locations are identified, the server mayconcatenate multiple instruction sets to ensure all damage locations arecaptured by the user in a single video. For example, if the damagelocations include the front bumper and the passenger side door, theserver 160 may obtain separate instruction sets for obtaining video dataof the bumper and for obtaining video data of the passenger side doorand may concatenate these instruction sets into a single instructionalvideo. An instruction set for obtaining video data of an identifier ofthe insured vehicle may always be concatenated to the beginning or endof other instruction sets to ensure the vehicle identifier is alwaysincluded in the instructions. The identifier may be the VIN and/or alicense plate number.

In another example, instruction sets may be concatenated in a randomorder such that each time instructions are obtained they may be in adifferent order. This may further help to prevent fraud. In anotherexample, the starting point and/or ending point may be selectedrandomly. For example, the first time video data is to be obtained of abumper, the starting point may be randomly set as the left hand side ofthe bumper. The next time video data is to be obtained of a bumper, thestarting point may be randomly set as the right hand side of the bumper.In another example, an instruction set for obtaining video data of anidentifier of the insured vehicle may be concatenated in a randomposition relative to the other instruction sets. For example,instructions may request that the identifier be obtained at thebeginning, middle or end of the instructions. As another example, theidentifier may be obtained at the beginning and end of the instructions.

An example display screen 900 is shown in FIG. 9. As can be seen, thedamage location has been identified as the driver side door of thevehicle. As a result, the server 160 sends, via the communicationsmodule, instructions in the form of video instructions to the remotecomputing device 100, shown as video instruction interface 910. The userof the remote computing device may play the video instructions byproviding input via the input interface. For example, the user mayperform a touch gesture at the location of the video instructioninterface 910. The video instructions include a video that shows theuser how to obtain video data of the vehicle at the damage location. Thevideo shows a starting point and ending point for obtaining video dataof the vehicle. The video may also show the user how to obtain videodata of the vehicle to obtain an identifier of the insured vehicle. Forexample, the video may start with a video on how to obtain video data ofthe VIN and then how to obtain video data of the vehicle at the damagelocation. Put another way, the instructions may indicate to the userthat the start point of the video is to obtain video data of the VIN.

Another example display screen 1000 is shown in FIGS. 10A to 10D. Inthis example, the damage locations have been identified as the driverside door and the rear bumper. As a result, the server 160 sends, viathe communications module, instructions in the form of videoinstructions to the remote computing device 100, shown as videoinstruction interface 1010. As can be seen, the video instructionsinstruct the user to obtain video data of the license plate (FIG. 10B),the driver side door (FIG. 10C) and then the rear bumper (FIG. 10D). Thevideo instructions include an arrow A indicating to the user aparticular direction that the video data should be obtained. It will beappreciated that the video instructions shown in FIGS. 10B to 10D arescreen shots of the video being played after the user has performed atouch gesture to play the video. A progress bar 1020 is shown in FIGS.10B to 10D indicating to the user how much time is left in theinstructional video.

The video data is received, via the communications module and from theremote computing device 100, by the server 160 (step 830).

The video data may be received by the server 160 after video datacapture has been completed by the user. In this example, a single videodata file may be received by the server 160. It will be appreciated thatonce the video data is received, the server 160 may ask the user ifthere are additional damage locations. If additional damage locationsexist, steps 810 and 820 may be repeated until all damage locations havebeen captured. Each time additional video data is to be captured, theinstructions may require the user to capture an identifier of thevehicle.

In an example where the video data is received by the server 160 aftervideo data capture has been completed by the user, the server 160 mayrequest that the user identify portions of the video data thatcorrespond to particular locations. For example, instructions may besent showing a video on how to obtain video data of the license plateand front bumper. Once the user obtains video data of the vehicle, theserver 160 may ask the user to enter a start time and an end time forwhen video data was captured of the license plate, and may ask the userto enter a start time and an end time for when video data was capturedof the bumper. The requests may be made in a chat interface. The server160 may then split the video data into different portions, specificallya vehicle identity portion and a vehicle damage portion. An example isshown on display screen 1100 in FIGS. 11A and 11B. As can be seen, thevideo data has been split into a vehicle identity portion 1110 and avehicle damage portion 1120 based on input received from the user. Theserver 160 may ask the user to review and decide whether or not videocapture needs to be re-done. Alternatively, the server may automaticallysplit the video data using video or image processing techniques.

The video data may be received by the server 160 in real-time. In thisexample, the video data obtained by the remote computing device 100 maybe sent, via the communications module, to the server 160 continuouslysuch that the server 160 receives the video data as a live or near livestream. The video data may be analyzed by the server 160 in real-time toensure the video data is being captured correctly. For example, thevideo data may be analyzed to ensure the user is capturing the videodata according to the instructions. As another example, the video datamay be analyzed to ensure the user is capturing the video data in thecorrect direction. As yet another example, the video data may beanalyzed to ensure the quality of the video data is sufficient forprocessing. If an error occurs, a prompt may be sent to the remotecomputing device indicating to the user that the video data capturesequence must restart.

In an example of the video data being received by the server 160 inreal-time, the server 160 may analyze the received video data and maysend, via the communications module and to the remote computing device100, data including a progress bar for display. An example displayscreen 1200 is shown in FIG. 12 wherein a video capture window 1210 anda progress bar 1220 are displayed. As can be seen, the user is capturingvideo data of the driver side of the vehicle. As the user walks from thefront to the back of the vehicle, the progress bar 1220 slides from astarting position (front of the vehicle) to an ending position (back ofthe vehicle). As will be appreciated, progress may be determined by theserver 160 by analyzing the received video data to determine a portionof the vehicle currently being captured. For example, identifyingfeatures may be identified in frames of the video data such as a fronttire, a door handle, etc. Progress may be determined by the server 160based on the instructions sent to the user. For example, a startingpoint and an ending point may be identified based on the instructionssent to the user and progress may be determined accordingly.

As will be appreciated, during video capture the remote computing device100 may automatically adjust camera settings. For example, the remotecomputing device 100 may automatically zoom in or out and/or mayautomatically focus. In another example, the remote computing device 100may automatically begin obtaining video data when, for example, alicense plate or VIN is detected through the camera by the server.Camera data obtained by the remote computing device 100 may becommunicated to the server 160 in real time and the camera data may beprocessed to identify the license plate or VIN of the insurance policydata and when identified, the server may prompt the remote computingdevice 100 to begin recording video data.

As another example of the video data being received by the server 160 inreal-time, the server 160 may receive, via the communications module andfrom the remote computing device 100, video data and sensor data inreal-time. In this example, the server 160 may analyze the receivedvideo data and sensor data to determine a location of the remotecomputing device 100 as it is obtaining video data. The location of theremote computing device 100 may be used to determine progress of thevideo data capture and the server may update a progress bar accordingly,similar to that described above. For example, in the event that a userwalks around the vehicle in a circle with the remote computing device100 while obtaining vehicle data, the location of the remote computingdevice 100 may be tracked and the progress may be estimated ordetermined accordingly. The sensor data may be mapped to portions of thecaptured video data which may help or simplify video data processing.

The video data is processed to confirm an identity of the vehicle and tonumerically quantify an amount of damage to the vehicle (step 840).

Various techniques may be employed to confirm the identity of thevehicle. For example, the instructions sent to the remote computingdevice may indicate to the user that the starting point of the video isto obtain the VIN. As such, the server 160 may analyze video dataobtained at the beginning of the video and may perform optical characterrecognition within the video data to identify text in the video data toobtain the VIN. The VIN obtained from the video data may be compared tothe VIN obtained from the insurance policy data and if there is a match,the identity of the vehicle is confirmed. Of course, if there is not amatch, an error may be sent from the server 160 via the communicationsmodule and to the remote computing device 100 indicating to the userthat the identity of the vehicle cannot be confirmed. As anotherexample, the server may obtain image data from the video data byselecting one or more frames therefrom. The image data may be analyzedby the server 160 by performing optical character recognition on theimage to identify text in the image. The text may be for example the VINor license plate and this may be compared to the insurance policy datato determine if there is a match. As will be appreciated, the identityof the vehicle may be confirmed while the video data is analyzed inreal-time during step 830. In real-time, if the identity of the vehicledoes not match the insurance policy data, an error may be sent to remotecomputing device and video data capture may be shut down.

Various techniques may be employed to numerically quantify the amount ofdamage to the vehicle. For example, photo-based estimation may be usedwherein the server 160 may obtain image data from the video data byselecting one or more frames or images therefrom. The image data maythen be analyzed by the server 160 to determine a location of any damagerepresented in the image and may determine an estimate based on thelocation of the damage and the type of vehicle.

As an example of photo-based estimation, the server 160 may analyze theimage data to obtain an indicator. The indicator may numericallyquantify an amount of damage to the insured vehicle. For example, theserver 160 may analyze the image data to obtain a damage quantumindicator. The damage quantum indicator may numerically quantify anamount of damage to the insured vehicle. For example, the damage quantumindicator may be an estimate of the value of a repair, replacement orclaim.

In determining the indicator, image processing techniques may comparethe vehicle in the image data to image data representing a base vehicle(i.e., an undamaged vehicle). The image data representing the basevehicle may, for example, including a mapping of parts. For example, theimage data representing the base vehicle may be an image of a vehiclewhich includes markers or identifiers indicating a part associated withvarious portions of the image. Upon identifying location(s) of thereceived image data that do not sufficiently correspond to similarlocations in the image data of the base vehicle, the server 160 maydetermine that such locations represent damaged components and may thenidentify the damaged components from the mapping of parts. A lookup maythen be performed in a database to determine a value associated with thedamaged components.

In the example shown in FIGS. 11A and 11B, the server 160 may analyzethe vehicle identity portion 1110 and the vehicle damage portion 1120.For example, the server 160 may obtain a single image frame from thevideo data during when the license plate was captured and may analyzethe single image frame to determine the license plate number. Similarly,the server 160 may obtain a single image from the video data during whenthe bumper was captured and may analyze the single image frame toquantify an amount of damage done to the vehicle.

The server 160 may then send, via the communications module and to theremote computing device 100, a numerical value based on the indicator.For example, the server 160 may send, via the communications module andto the remote computing device, a numerical value based on the damagequantum indicator. The numerical value may, for example, be an estimate.

In embodiments of photo-based estimation described above, imageprocessing techniques are described wherein image data of a vehicle iscompared to image data representing a base vehicle (i.e. an undamagedvehicle). In some embodiments, comparing image data to image data of anundamaged vehicle may not be accurate as a vehicle may have obtainedprevious damage prior to filing a claim and/or the vehicle may haveafter-market upgrades or modifications. As such, video or image data ofa vehicle may be obtained during onboarding before an insurance policyhas begun. An exemplary method of onboarding a vehicle is shown in FIG.13 and is generally identified by reference numeral 1300. The operationsin method 1300 are performed by server 160. More specifically,computer-executable instructions stored in memory of the server 160 may,when executed by a processor of the server 160, configure the server 160to perform the method 1300 or a portion thereof.

The method 1300 begins when a request is received from a remotecomputing device to initiate a chat session (step 1310). In thisembodiment, the chat session may be initiated by a user of the remotecomputing device during the process of insuring a vehicle. The chatsession may be requested through an internet interface, mobileapplication, etc. In this example, it is assumed that the identifyinginformation of the user and the vehicle were previously obtained by theserver 160. However, as will be appreciated, this information may beobtained using the chat session.

In response, the server 160 provides a chat interface to the remotecomputing device 100 (step 1320). In this embodiment, the server 160sends, via the communications module and to the remote computing device100, data that includes a chat interface. An example chat interface 1400is shown in FIG. 14.

During the chat session, the server 160 requests and receives video dataof a vehicle in an original state (step 1330). In the example shown inFIG. 14, the server 160 communicates instructions in the form of videoinstructions 1410 to the remote computing device and asks the user toobtain video data of the vehicle, similar to that described above. Thevideo instructions may include a starting point and an ending point,similar to that described above. The video instructions may request thatthe user capture video data of the VIN or license plate of the vehicle,similar to that described above. As will be appreciated, in anotherexample the server may request that video data be obtained using aparticular camera such as for example a 3D camera (e.g. Mantis Visiontechnology). The vehicle may be brand new or may have damage. As such,the original state is the state that the vehicle is in at the time ofonboarding.

As will be appreciated, other features described above may be utilizedsuch as for example the use of a progress bar and/or sensor data.

Once received, the server 160 may analyze the video data of the vehiclein the original state according to a method 1500 shown in FIG. 15. Theoperations in method 1500 are performed by server 160. Morespecifically, computer-executable instructions stored in memory of theserver 160 may, when executed by a processor of the server 160,configure the server 160 to perform the method 1500 or a portionthereof.

During method 1500, the video data is analyzed to identify anypre-existing damage and to identify any after-market modifications (step1510). In this embodiment, the video data is analyzed in a similarmanner to that described in step 840 of method 800 in that one or moreframes of the video data of the vehicle in the original state may beobtained and compared to image data representing a base vehicle (i.e. anundamaged vehicle).

If any pre-existing damage or after-market modifications are identified,the server confirms the pre-existing damage or after-marketmodifications with the user (step 1520). For example, the server may askthe user to confirm damage or after-market modifications within the chatinterface.

An example chat interface 1600 is shown in FIG. 16. As can be seen, theserver confirms receipt of the video data of the vehicle. In thisexample, during step 1510 the server analyzes the video data andidentifies damage to the driver side door. The server provides an imageobtained from the video data and asks the user to confirm that there isindeed damage to the passenger side door.

Once pre-existing damage and/or after-market modifications areconfirmed, the server 160 stores image data or video data associatedwith the pre-existing damage and/or after-market modifications in memory(step 1530). The server may also store data regarding the damage. Thedata may include a day/time that the damage was confirmed. The data mayalso include a screen-shot of the user confirming the damage and/orafter-market modification. The server may generate a 3D model of thevehicle that includes the pre-existing damage and/or after-marketmodifications. The 3D model may be used in a manner similar to thatdescribed above.

The server 160 may analyze the video data and segment the video datainto different parts or frames. For example, the server 160 may identifythe VIN or license plate of the vehicle, using techniques describedabove, and may store a frame or a part of the video data that shows theVIN or license plate in the memory. Further, the server 160 may identifya passenger door in the video data and may store a frame or a part ofthe video data that shows the passenger door. Each stored frame or partof video data may be labelled with a descriptor such as for example“passenger door” or “license plate”.

The video or image data obtained of the vehicle in the original state(during onboarding) may be used to facilitate photo-based estimation.For example, damage indicated during onboarding may be taken intoconsideration during photo-based estimation such that any pre-existingdamage is not included in the estimate.

As another example, in the event that a user submits a claim, video orimage data obtained during onboarding may be used to instruct the userhow to obtain video data of the vehicle. An example method 1700 wherevideo or image data obtained during onboarding is used to instruct auser is shown in FIG. 17. The operations in method 1700 are performed byserver 160. More specifically, computer-executable instructions storedin memory of the server 160 may, when executed by a processor of theserver 160, configure the server 160 to perform the method 1700 or aportion thereof.

The method begins when an indication of a claim is received by theserver 160, the indication associated with an identifier (step 1710).The indication may be received from the remote computing device 100 inmanners described above, for example during a chat session or in theevent a user opens up a mobile application. The identifier may be apolicy number, a name, address, contact information, a token, a PIN, auser name, biometric data, a password, etc.

Video or image data of the vehicle in the original state is retrievedfrom the memory (step 1720). The video or image data is obtained usingthe identifier. For example, video or image data stored duringonboarding of the vehicle may be retrieved using the policy number.

Instructions for obtaining video or image data of the vehicle are sentto the remote computing device based on the video or image data of thevehicle in the original state (step 1730). The instructions may be videoinstructions, photo instructions and/or text instructions. Theinstructions may include a starting point and an ending point for videocapture which may correspond to starting and ending points in the videoor image data obtained of the vehicle in the original state.

For example, in the case where descriptors are used in a chat-basedenvironment, the user may text that “the passenger door is damaged” andthe server may obtain the “passenger door” frame or video data that wasobtained during onboarding. The “passenger door” frame or video data maybe sent to the remote computing device 100 and the server 160 may askthe user to capture image or video data of the damaged passenger doorsuch that the captured image or video data has a similar view orstart/end point as the “passenger door” frame or video data captured inthe original state.

Once video or image data is obtained of the vehicle when submitting aclaim, video or image data of the vehicle in the original state may beused to more accurately conduct photo-based estimation. For example,video or image data of a passenger door at the original state (obtainedduring on-boarding) may be compared to video or image data of thedamaged passenger door to more accurately estimate a cost of repair.Since the video or image data of the passenger door is taken from asimilar view or start/end point, processing and/or comparing the videoor image data of the passenger door in the original state to the damagedpassenger door is simplified and more efficient. As another example, theserver may compare frames of video data obtained of the vehicle in theoriginal state to frames of video data obtained of the vehicle in thedamaged state. Since the user was instructed on how to obtain video dataof the vehicle to match video data obtained of the vehicle in theoriginal state, video or image processing is simplified.

It will be appreciated that video data obtained of the vehicle at theoriginal state may be used, for example, during step 820 of method 800such that the instructions sent to the user are based on video dataobtained of the vehicle in the original state.

Although embodiments described above relate to vehicle insuranceonboarding and/or claims processing, those skilled in the art willappreciate that at least some of the above embodiments may be used whena user rents or leases a vehicle. For example, when a user picks up avehicle for rent, the user may capture video or image data of thevehicle in an original state. When the user drops the vehicle off, theuser may capture video or image data of the vehicle in a returned state.The original state may be automatically compared to the returned stateto determine if any damage has been done to the vehicle. An estimate ofthe damage done may be automatically determined using photo-basedestimation as described above.

As will be appreciated, at least some of the above embodiments andexamples may be implemented within a mobile application installed on theremote computing device. The mobile application may include otherfeatures some of which may be based on the geographical location of theremote computing device. For example, the server may associate ageographical location each time an insurance claim is processed or madethrough the mobile application. In the event that a particulargeographical location is associated with multiple insurance claims, suchas for example vehicle theft or vandalism, the server may flag thisgeographical location as being high-risk. The server may monitor thelocation of remote computing devices associated with users that haveinstalled the mobile application and may send a warning or indication tothe remote computing device informing the user that they are in ahigh-risk location. The warning or indication may offer to direct theuser to a lower risk area. The server may also monitor the location ofremote computing devices associated with users that have installed themobile application and may inform them of potential parking violations,etc.

In embodiments described above, obtaining video data using the remotecomputing device is described. Those skilled in the art will appreciatethat other camera, image or video devices may be used to obtain videodata in 2D or 3D.

In some embodiments, the server 160 and the remote computing device 100may communicate through encrypted communications and the server 160 mayonly receive video data obtained through such encrypted communications.

In some instances, there may be a lag between a time when video data isobtained and a time when the video data is sent to the server. Such alag may be caused, for example, because a user may be provided with anopportunity to review the video data or because a user may wish to waitto upload the video data until they are connected to Wi-Fi. The lag mayprovide an opportunity for tampering in at least some situations. Insome embodiments, in order to prevent tampering, a hash, such as SHA-256hash may be performed immediately after the video data is obtained andmay be sent to the server. Later, after the server receives the videodata, the server may use the hash to confirm that the received videodata is the original video data.

The methods described above may be modified and/or operations of suchmethods combined to provide other methods.

Furthermore, while the description above generally refers to vehicles,any reference to a vehicle could be replaced with other property.

Furthermore, the description above generally describes operations thatmay be performed by a server and a remote computing device incooperation with one another. Operations that are described as beingperformed by the server may, instead, be performed by the remotecomputing device.

Example embodiments of the present application are not limited to anyparticular operating system, system architecture, mobile devicearchitecture, server architecture, or computer programming language.

It will be understood that the applications, modules, routines,processes, threads, or other software components implementing thedescribed method/process may be realized using standard computerprogramming techniques and languages. The present application is notlimited to particular processors, computer languages, computerprogramming conventions, data structures, or other such implementationdetails. Those skilled in the art will recognize that the describedprocesses may be implemented as a part of computer-executable codestored in volatile or non-volatile memory, as part of anapplication-specific integrated chip (ASIC), etc.

As noted, certain adaptations and modifications of the describedembodiments can be made. Therefore, the above discussed embodiments areconsidered to be illustrative and not restrictive.

What is claimed is:
 1. A server comprising: a communications module; aprocessor coupled to the communications module; and a memory coupled tothe processor, the memory storing processor-executable instructionswhich, when executed by the processor, configure the processor to:receive, via the communications module and from a remote computingdevice, video data of a vehicle in an original state; store, in thememory, at least some of the video data of the vehicle and associate thestored video data with an account; receive, via the communicationsmodule and from the remote computing device, an indication of a claim,the indication associated with an account identifier; retrieve, usingthe account identifier and from the memory, the video data of thevehicle in the original state from the memory; and send, via thecommunications module and to the remote computing device, instructionsfor obtaining video data of the vehicle based on the video data of thevehicle in the original state.
 2. The server of claim 1, wherein theindication of the claim includes an indication of a damage location ofthe vehicle.
 3. The server of claim 2, wherein the instructions forobtaining video data of the vehicle include instructions for obtainingvideo data of the vehicle at the damage location.
 4. The server of claim3, wherein the instructions for obtaining video data of the vehicleinclude an indication of a starting point and an ending point for videocapture.
 5. The server of claim 1, wherein the instructions forobtaining video data of the vehicle include instructions for capturingan identifier of the vehicle.
 6. The server of claim 1, wherein theprocessor-executable instructions, when executed by the processor,further configure the processor to: receive, via the communicationsmodule and from the remote computing device, video data of the vehiclecaptured in response to the instructions; and process the video data tonumerically quantify an amount of damage to the vehicle.
 7. The serverof claim 1, wherein the processor-executable instructions, when executedby the processor, further configure the processor to: receive, via thecommunications module and from the remote computing device, video dataof the vehicle captured in response to the instructions; and process thevideo data to confirm an identity of the vehicle.
 8. The server of claim1, wherein the processor-executable instructions, when executed by theprocessor, further configure the processor to: process the video data ofthe vehicle in the original state to identify at least one ofpre-existing damage to the vehicle and aftermarket modifications made tothe vehicle.
 9. The server of claim 1, wherein the processor-executableinstructions, when executed by the processor, further configure theprocessor to: generate a three-dimensional model of the vehicle based atleast on the video data of the vehicle in the original state.
 10. Theserver of claim 9, wherein the instructions for obtaining video data ofthe vehicle are further based on the three-dimensional model of thevehicle.
 11. A method comprising: receiving, via a communications moduleand from a remote computing device, video data of a vehicle in anoriginal state; storing at least some of the video data of the vehiclein memory and associating the stored video data with an account;receiving, via the communications module and from the remote computingdevice, an indication of a claim, the indication associated with anaccount identifier; retrieving, using the account identifier and fromthe memory, the video data of the vehicle in the original state from thememory; and sending, via the communications module and to the remotecomputing device, instructions for obtaining video data of the vehiclebased on the video data of the vehicle in the original state.
 12. Themethod of claim 11, wherein the instructions for obtaining video data ofthe vehicle include instructions for obtaining video data of the vehicleat the damage location.
 13. The method of claim 12, wherein theinstructions for obtaining video data of the vehicle include anindication of a starting point and an ending point for video capture.14. The method of claim 11, wherein the instructions for obtaining videodata of the vehicle include instructions for capturing an identifier ofthe vehicle.
 15. The method of claim 11, further comprising: receiving,via the communications module and from the remote computing device,video data of the vehicle captured in response to the instructions; andprocessing the video data to numerically quantify an amount of damage tothe vehicle.
 16. The method of claim 11, further comprising: receiving,via the communications module and from the remote computing device,video data of the vehicle captured in response to the instructions; andprocessing the video data to confirm an identity of the vehicle.
 17. Themethod of claim 11, further comprising: processing the video data of thevehicle in the original state to identify at least one of pre-existingdamage to the vehicle and aftermarket modifications made to the vehicle.18. The method of claim 11, further comprising: generating athree-dimensional model of the vehicle based at least on the video dataof the vehicle in the original state.
 19. The method of claim 18,wherein the instructions for obtaining video data of the vehicle arefurther based on the three-dimensional model of the vehicle.
 20. Anon-transitory computer readable storage medium comprisingcomputer-executable instructions which, when executed, configure acomputing device to: receive, via a communications module and from aremote computing device, video data of a vehicle in an original state;store, in memory, at least some of the video data of the vehicle andassociate the stored video data with an account; receive, via thecommunications module and from the remote computing device, anindication of a claim, the indication associated with an accountidentifier; retrieve, using the account identifier and from the memory,the video data of the vehicle in the original state from the memory; andsend, via the communications module and to the remote computing device,instructions for obtaining video data of the vehicle based on the videodata of the vehicle in the original state.